Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	145460
Missing cells	4032
Missing cells (%)	0.2%
Duplicate rows	2
Duplicate rows (%)	< 0.1%
Total size in memory	16.6 MiB
Average record size in memory	120.0 B

Variable types

Categorical	4
Numeric	8
Boolean	2

Alerts

Dataset has 2 (< 0.1%) duplicate rows	Duplicates
`MinTemp` is highly correlated with `MaxTemp`	High correlation
`MaxTemp` is highly correlated with `MinTemp`	High correlation
`MinTemp` is highly correlated with `MaxTemp`	High correlation
`MaxTemp` is highly correlated with `MinTemp`	High correlation
`MinTemp` is highly correlated with `MaxTemp`	High correlation
`MaxTemp` is highly correlated with `MinTemp`	High correlation
`Location` is highly correlated with `MinTemp` and 6 other fields	High correlation
`MinTemp` is highly correlated with `Location` and 1 other fields	High correlation
`MaxTemp` is highly correlated with `Location` and 1 other fields	High correlation
`WindGustDir` is highly correlated with `Location` and 2 other fields	High correlation
`WindDir9am` is highly correlated with `Location` and 2 other fields	High correlation
`WindDir3pm` is highly correlated with `Location` and 2 other fields	High correlation
`NewHumidity` is highly correlated with `Location` and 1 other fields	High correlation
`NewTemp` is highly correlated with `Location` and 1 other fields	High correlation
`Rainfall` has 92924 (63.9%) zeros	Zeros

Reproduction

Analysis started	2022-02-28 08:24:11.255255
Analysis finished	2022-02-28 08:24:52.278142
Duration	41.02 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Location
Categorical

HIGH CORRELATION

Distinct	49
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	2.2 MiB

Canberra	3436
Sydney	3344
Brisbane	3193
Darwin	3193
Melbourne	3193
Other values (44)	128813

Length

Max length	16
Median length	8
Mean length	8.711039319
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Albury
2nd row	Albury
3rd row	Albury
4th row	Albury
5th row	Albury

Common Values

Value	Count	Frequency (%)
Canberra	3436	2.4%
Sydney	3344	2.3%
Brisbane	3193	2.2%
Darwin	3193	2.2%
Melbourne	3193	2.2%
Adelaide	3193	2.2%
Perth	3193	2.2%
Hobart	3193	2.2%
GoldCoast	3040	2.1%
Cairns	3040	2.1%
Other values (39)	113154	77.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
canberra	3436	2.4%
sydney	3344	2.3%
brisbane	3193	2.2%
darwin	3193	2.2%
melbourne	3193	2.2%
adelaide	3193	2.2%
perth	3193	2.2%
hobart	3193	2.2%
townsville	3040	2.1%
alicesprings	3040	2.1%
Other values (39)	113154	77.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

MinTemp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	389
Distinct (%)	0.3%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	12.21289298

Minimum	-8.5
Maximum	33.9
Zeros	161
Zeros (%)	0.1%
Negative	3501
Negative (%)	2.4%
Memory size	2.2 MiB

Quantile statistics

Minimum	-8.5
5-th percentile	1.8
Q1	7.6
median	12
Q3	16.9
95-th percentile	23
Maximum	33.9
Range	42.4
Interquartile range (IQR)	9.3

Descriptive statistics

Standard deviation	6.396455664
Coefficient of variation (CV)	0.5237461487
Kurtosis	-0.4843906492
Mean	12.21289298
Median Absolute Deviation (MAD)	4.6
Skewness	0.01343422194
Sum	1772970.1
Variance	40.91464506
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17.6	1074	0.7%
11	906	0.6%
10.2	901	0.6%
9.6	900	0.6%
12	891	0.6%
10.5	887	0.6%
10	878	0.6%
10.8	876	0.6%
9	873	0.6%
8.9	865	0.6%
Other values (379)	136121	93.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-8.5	1	< 0.1%
-8.2	2	< 0.1%
-8	2	< 0.1%
-7.8	1	< 0.1%
-7.6	2	< 0.1%
-7.5	2	< 0.1%
-7.3	1	< 0.1%
-7.2	1	< 0.1%
-7.1	1	< 0.1%
-7	8	< 0.1%

Value	Count	Frequency (%)
33.9	1	< 0.1%
31.9	1	< 0.1%
31.8	1	< 0.1%
31.4	3	< 0.1%
31.2	1	< 0.1%
31	1	< 0.1%
30.7	2	< 0.1%
30.5	1	< 0.1%
30.3	1	< 0.1%
30.2	1	< 0.1%

MaxTemp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	505
Distinct (%)	0.3%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	23.22418717

Minimum	-4.8
Maximum	48.1
Zeros	15
Zeros (%)	< 0.1%
Negative	114
Negative (%)	0.1%
Memory size	2.2 MiB

Quantile statistics

Minimum	-4.8
5-th percentile	12.9
Q1	18
median	22.7
Q3	28.2
95-th percentile	35.5
Maximum	48.1
Range	52.9
Interquartile range (IQR)	10.2

Descriptive statistics

Standard deviation	7.110371109
Coefficient of variation (CV)	0.3061623237
Kurtosis	-0.2135362797
Mean	23.22418717
Median Absolute Deviation (MAD)	5.1
Skewness	0.2184859211
Sum	3371501.7
Variance	50.55737731
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
23.9	1152	0.8%
20	893	0.6%
19.8	846	0.6%
19	846	0.6%
20.4	834	0.6%
19.9	827	0.6%
20.8	823	0.6%
18.5	817	0.6%
19.5	813	0.6%
21	812	0.6%
Other values (495)	136509	93.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-4.8	1	< 0.1%
-4.1	1	< 0.1%
-3.8	1	< 0.1%
-3.7	1	< 0.1%
-3.2	1	< 0.1%
-3.1	2	< 0.1%
-3	1	< 0.1%
-2.9	1	< 0.1%
-2.7	1	< 0.1%
-2.5	2	< 0.1%

Value	Count	Frequency (%)
48.1	1	< 0.1%
47.3	2	< 0.1%
47	1	< 0.1%
46.9	1	< 0.1%
46.8	3	< 0.1%
46.7	2	< 0.1%
46.6	1	< 0.1%
46.5	1	< 0.1%
46.4	4	< 0.1%
46.3	2	< 0.1%

Rainfall
Real number (ℝ_≥0)

ZEROS

Distinct	681
Distinct (%)	0.5%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	2.37929215

Minimum	0
Maximum	371
Zeros	92924
Zeros (%)	63.9%
Negative	0
Negative (%)	0.0%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0.8
95-th percentile	13.2
Maximum	371
Range	371
Interquartile range (IQR)	0.8

Descriptive statistics

Standard deviation	8.485728267
Coefficient of variation (CV)	3.566492777
Kurtosis	175.0343015
Mean	2.37929215
Median Absolute Deviation (MAD)	0
Skewness	9.734401759
Sum	345406.6
Variance	72.00758421
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	92924	63.9%
0.2	8904	6.1%
0.4	3834	2.6%
0.6	2632	1.8%
0.8	2107	1.4%
1	1781	1.2%
1.2	1570	1.1%
1.4	1404	1.0%
1.6	1217	0.8%
1.8	1129	0.8%
Other values (671)	27670	19.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	92924	63.9%
0.1	162	0.1%
0.2	8904	6.1%
0.3	66	< 0.1%
0.4	3834	2.6%
0.5	39	< 0.1%
0.6	2632	1.8%
0.7	13	< 0.1%
0.8	2107	1.4%
0.9	15	< 0.1%

Value	Count	Frequency (%)
371	1	< 0.1%
367.6	1	< 0.1%
278.4	1	< 0.1%
268.6	1	< 0.1%
247.2	1	< 0.1%
240	1	< 0.1%
236.8	1	< 0.1%
225	1	< 0.1%
219.6	1	< 0.1%
216.3	1	< 0.1%

WindGustDir
Categorical

HIGH CORRELATION

Distinct	16
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	2.2 MiB

W	17417
SE	9613
N	9421
SSE	9366
E	9342
Other values (11)	90013

Length

Max length	3
Median length	2
Mean length	2.136562147
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	WSW
2nd row	NE
3rd row	W
4th row	WNW
5th row	W

Common Values

Value	Count	Frequency (%)
W	17417	12.0%
SE	9613	6.6%
N	9421	6.5%
SSE	9366	6.4%
E	9342	6.4%
S	9307	6.4%
WSW	9212	6.3%
SW	9182	6.3%
SSW	8842	6.1%
WNW	8424	5.8%
Other values (6)	45046	31.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
w	17417	12.0%
se	9613	6.6%
n	9421	6.5%
sse	9366	6.5%
e	9342	6.4%
s	9307	6.4%
wsw	9212	6.3%
sw	9182	6.3%
ssw	8842	6.1%
wnw	8424	5.8%
Other values (6)	45046	31.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

WindGustSpeed
Real number (ℝ_≥0)

Distinct	67
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	39.46457306

Minimum	6
Maximum	135
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.2 MiB

Quantile statistics

Minimum	6
5-th percentile	19
Q1	30
median	37
Q3	46
95-th percentile	65
Maximum	135
Range	129
Interquartile range (IQR)	16

Descriptive statistics

Standard deviation	13.62464802
Coefficient of variation (CV)	0.3452374362
Kurtosis	1.427839318
Mean	39.46457306
Median Absolute Deviation (MAD)	7
Skewness	0.8808702838
Sum	5729151
Variance	185.6310337
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
33	11115	7.6%
35	9632	6.6%
37	9154	6.3%
39	8917	6.1%
31	8565	5.9%
41	7504	5.2%
30	7168	4.9%
43	6864	4.7%
28	6597	4.5%
44	5739	3.9%
Other values (57)	63917	43.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6	1	< 0.1%
7	19	< 0.1%
9	92	0.1%
11	196	0.1%
13	534	0.4%
15	841	0.6%
17	1406	1.0%
19	4716	3.2%
20	2667	1.8%
22	2849	2.0%

Value	Count	Frequency (%)
135	3	< 0.1%
130	1	< 0.1%
126	2	< 0.1%
124	2	< 0.1%
122	3	< 0.1%
120	4	< 0.1%
117	4	< 0.1%
115	5	< 0.1%
113	8	< 0.1%
111	3	< 0.1%

WindDir9am
Categorical

HIGH CORRELATION

Distinct	16
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	2.2 MiB

N	12496
NW	10248
SE	10027
E	9679
SSE	9679
Other values (11)	93043

Length

Max length	3
Median length	2
Mean length	2.180764886
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	W
2nd row	SE
3rd row	ENE
4th row	W
5th row	SW

Common Values

Value	Count	Frequency (%)
N	12496	8.6%
NW	10248	7.0%
SE	10027	6.9%
E	9679	6.7%
SSE	9679	6.7%
SW	9317	6.4%
S	9301	6.4%
W	9024	6.2%
NNE	8661	6.0%
NNW	8485	5.8%
Other values (6)	48255	33.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
n	12496	8.6%
nw	10248	7.1%
se	10027	6.9%
sse	9679	6.7%
e	9679	6.7%
sw	9317	6.4%
s	9301	6.4%
w	9024	6.2%
nne	8661	6.0%
nnw	8485	5.8%
Other values (6)	48255	33.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

WindDir3pm
Categorical

HIGH CORRELATION

Distinct	16
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	2.2 MiB

SE	11928
W	10268
SW	10178
S	10003
WSW	9629
Other values (11)	93166

Length

Max length	3
Median length	2
Mean length	2.207484914
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	WSW
2nd row	E
3rd row	NW
4th row	W
5th row	W

Common Values

Value	Count	Frequency (%)
SE	11928	8.2%
W	10268	7.1%
SW	10178	7.0%
S	10003	6.9%
WSW	9629	6.6%
SSE	9485	6.5%
WNW	9469	6.5%
N	9004	6.2%
NW	8847	6.1%
ESE	8574	5.9%
Other values (6)	47787	32.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
se	11928	8.2%
w	10268	7.1%
sw	10178	7.0%
s	10003	6.9%
wsw	9629	6.6%
sse	9485	6.5%
wnw	9469	6.5%
n	9004	6.2%
nw	8847	6.1%
ese	8574	5.9%
Other values (6)	47787	32.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

RainToday
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	1.4 MiB

False	112477
True	32695
(Missing)	288

Common Values
Chart

Value	Count	Frequency (%)
False	112477	77.3%
True	32695	22.5%
(Missing)	288	0.2%

RainTomorrow
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	288
Missing (%)	0.2%
Memory size	1.4 MiB

False	112480
True	32692
(Missing)	288

Common Values
Chart

Value	Count	Frequency (%)
False	112480	77.3%
True	32692	22.5%
(Missing)	288	0.2%

NewWindSpeed
Real number (ℝ_≥0)

Distinct	127
Distinct (%)	0.1%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	16.45142314

Minimum	0
Maximum	88
Zeros	505
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	5.5
Q1	11
median	15.5
Q3	21
95-th percentile	30.5
Maximum	88
Range	88
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	7.750668259
Coefficient of variation (CV)	0.4711244853
Kurtosis	1.057709798
Mean	16.45142314
Median Absolute Deviation (MAD)	5
Skewness	0.7196467507
Sum	2388286
Variance	60.07285846
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13	7194	4.9%
14	6633	4.6%
12	6311	4.3%
15	5553	3.8%
19.5	5402	3.7%
11	5381	3.7%
18.5	5353	3.7%
17.5	4513	3.1%
16	4475	3.1%
10	4139	2.8%
Other values (117)	90218	62.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	505	0.3%
1	351	0.2%
2	813	0.6%
3	1033	0.7%
3.5	854	0.6%
4	868	0.6%
4.5	1752	1.2%
5	621	0.4%
5.5	2401	1.7%
6	513	0.4%

Value	Count	Frequency (%)
88	1	< 0.1%
83	1	< 0.1%
80.5	1	< 0.1%
69.5	2	< 0.1%
69	1	< 0.1%
66.5	3	< 0.1%
65	1	< 0.1%
63	1	< 0.1%
62	1	< 0.1%
61.5	1	< 0.1%

NewHumidity
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	200
Distinct (%)	0.1%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	60.17328066

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	2.2 MiB

Quantile statistics

Minimum	0
5-th percentile	27
Q1	48.5
median	61.5
Q3	73
95-th percentile	88.5
Maximum	100
Range	100
Interquartile range (IQR)	24.5

Descriptive statistics

Standard deviation	18.26111578
Coefficient of variation (CV)	0.3034754892
Kurtosis	-0.1009034926
Mean	60.17328066
Median Absolute Deviation (MAD)	12
Skewness	-0.3595674717
Sum	8735475.5
Variance	333.4683497
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
61	2102	1.4%
62	1731	1.2%
66	1665	1.1%
63.5	1665	1.1%
64	1662	1.1%
60.5	1637	1.1%
58.5	1628	1.1%
64.5	1627	1.1%
59.5	1621	1.1%
63	1613	1.1%
Other values (190)	128221	88.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	197	0.1%
1.5	2	< 0.1%
2	4	< 0.1%
2.5	6	< 0.1%
3	6	< 0.1%
3.5	12	< 0.1%
4	16	< 0.1%
4.5	12	< 0.1%
5	24	< 0.1%

Value	Count	Frequency (%)
100	230	0.2%
99.5	135	0.1%
99	199	0.1%
98.5	176	0.1%
98	301	0.2%
97.5	177	0.1%
97	231	0.2%
96.5	177	0.1%
96	253	0.2%
95.5	269	0.2%

NewPressure
Real number (ℝ_≥0)

Distinct	1407
Distinct (%)	1.0%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	1016.708898

Minimum	979.75
Maximum	1040.05
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	2.2 MiB

Quantile statistics

Minimum	979.75
5-th percentile	1005.6
Q1	1012.3
median	1016.75
Q3	1021.05
95-th percentile	1027.75
Maximum	1040.05
Range	60.3
Interquartile range (IQR)	8.75

Descriptive statistics

Standard deviation	6.847634479
Coefficient of variation (CV)	0.006735098405
Kurtosis	0.239444936
Mean	1016.708898
Median Absolute Deviation (MAD)	4.4
Skewness	-0.07660944875
Sum	147597664.2
Variance	46.89009796
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1017.25	3433	2.4%
1019.35	3171	2.2%
1014.65	3170	2.2%
1027.3	3034	2.1%
1014.8	1482	1.0%
1019.8	828	0.6%
1020.2	686	0.5%
1013.4	513	0.4%
1011.55	452	0.3%
1016.25	401	0.3%
Other values (1397)	128002	88.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
979.75	1	< 0.1%
981.05	1	< 0.1%
982.05	1	< 0.1%
982.6	2	< 0.1%
983.05	1	< 0.1%
984	1	< 0.1%
984.2	1	< 0.1%
984.35	1	< 0.1%
984.5	1	< 0.1%
984.75	1	< 0.1%

Value	Count	Frequency (%)
1040.05	1	< 0.1%
1039.65	1	< 0.1%
1039.55	1	< 0.1%
1039.35	1	< 0.1%
1039.25	2	< 0.1%
1039.15	1	< 0.1%
1039.05	1	< 0.1%
1039	1	< 0.1%
1038.95	2	< 0.1%
1038.9	1	< 0.1%

NewTemp
Real number (ℝ)

HIGH CORRELATION

Distinct	1437
Distinct (%)	1.0%
Missing	288
Missing (%)	0.2%
Infinite	0
Infinite (%)	0.0%
Mean	19.3338774

Minimum	-6.3
Maximum	41.6
Zeros	7
Zeros (%)	< 0.1%
Negative	286
Negative (%)	0.2%
Memory size	2.2 MiB

Quantile statistics

Minimum	-6.3
5-th percentile	9.55
Q1	14.55
median	19
Q3	23.9
95-th percentile	30.3
Maximum	41.6
Range	47.9
Interquartile range (IQR)	9.35

Descriptive statistics

Standard deviation	6.484813552
Coefficient of variation (CV)	0.3354119517
Kurtosis	-0.2798084092
Mean	19.3338774
Median Absolute Deviation (MAD)	4.65
Skewness	0.1245190398
Sum	2806737.65
Variance	42.05280681
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
21.55	614	0.4%
17.25	479	0.3%
16.4	467	0.3%
16.35	463	0.3%
17	448	0.3%
15.75	448	0.3%
17.5	446	0.3%
20.5	446	0.3%
18.85	444	0.3%
19.75	444	0.3%
Other values (1427)	140473	96.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-6.3	1	< 0.1%
-5.5	1	< 0.1%
-5.25	1	< 0.1%
-4.95	1	< 0.1%
-4.75	1	< 0.1%
-4.65	1	< 0.1%
-4.6	1	< 0.1%
-4.45	1	< 0.1%
-4.4	1	< 0.1%
-4.35	1	< 0.1%

Value	Count	Frequency (%)
41.6	1	< 0.1%
41.25	1	< 0.1%
41.1	1	< 0.1%
41.1	1	< 0.1%
40.9	1	< 0.1%
40.8	1	< 0.1%
40.75	2	< 0.1%
40.7	1	< 0.1%
40.5	1	< 0.1%
40.45	1	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Location	MinTemp	MaxTemp	Rainfall	WindGustDir	WindGustSpeed	WindDir9am	WindDir3pm	RainToday	RainTomorrow	NewWindSpeed	NewHumidity	NewPressure	NewTemp
0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	22.5	34.0	1008.15	22.10
1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	10.0	30.5	1015.20	22.30
2	Albury	12.9	25.7	0.0	WSW	46.0	W	WSW	No	No	13.5	57.5	1008.40	23.75
3	Albury	9.2	28.0	0.0	NE	24.0	SE	E	No	No	21.5	39.0	1007.30	24.75
4	Albury	17.5	32.3	1.0	W	41.0	ENE	NW	No	No	22.0	34.0	1008.90	21.35
5	Albury	14.6	29.7	0.2	WNW	56.0	W	W	No	No	11.5	33.5	1011.75	20.90
6	Albury	14.3	25.0	0.0	W	50.0	SW	W	No	No	17.5	25.5	1006.25	24.25
7	Albury	7.7	26.7	0.0	W	35.0	SSE	W	No	No	13.0	42.5	1006.35	24.15
8	Albury	9.7	31.9	0.0	NNW	80.0	SE	NW	No	Yes	11.5	35.0	1010.25	24.60
9	Albury	13.1	30.1	1.4	W	28.0	S	SSE	Yes	No	14.0	90.0	1007.35	16.45

Last rows

	Location	MinTemp	MaxTemp	WindGustDir	WindGustSpeed	WindDir9am	WindDir3pm	RainToday	RainTomorrow	NewWindSpeed	NewHumidity	NewPressure	NewTemp
145450	Uluru	5.2	24.3	E	24.0	SE	E	No	No	NaN	NaN	NaN	NaN
145451	Uluru	6.4	23.4	ESE	31.0	S	ESE	No	No	NaN	NaN	NaN	NaN
145452	Uluru	8.0	20.7	ESE	41.0	SE	E	No	No	NaN	NaN	NaN	NaN
145453	Uluru	7.4	20.6	E	35.0	ESE	E	No	No	NaN	NaN	NaN	NaN
145454	Uluru	3.5	21.8	E	31.0	ESE	E	No	No	NaN	NaN	NaN	NaN
145455	Uluru	2.8	23.4	E	31.0	SE	ENE	No	No	NaN	NaN	NaN	NaN
145456	Uluru	3.6	25.3	NNW	22.0	SE	N	No	No	NaN	NaN	NaN	NaN
145457	Uluru	5.4	26.9	N	37.0	SE	WNW	No	No	NaN	NaN	NaN	NaN
145458	Uluru	7.8	27.0	SE	28.0	SSE	N	No	No	NaN	NaN	NaN	NaN
145459	Uluru	14.9	27.0	SE	28.0	ESE	ESE	No	No	NaN	NaN	NaN	NaN

Most frequently occurring

	Location	MinTemp	MaxTemp	Rainfall	WindGustDir	WindGustSpeed	WindDir9am	WindDir3pm	RainToday	RainTomorrow	NewWindSpeed	NewHumidity	NewPressure	NewTemp	# duplicates
0	Melbourne	17.6	23.9	0.0	S	31.0	S	S	No	No	18.5	61.0	1019.80	21.55	2
1	MountGinini	-0.2	9.2	0.0	SW	35.0	N	WNW	No	No	16.5	30.0	1017.25	14.10	2

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows

Duplicate rows

Most frequently occurring